Characterization of equilibrative nucleoside transport of the pancreatic cancer cell line: Panc-1
Bibliographic record
Abstract
Objectives: Gemcitabine, a first-line chemotherapeutic nucleoside analog drug (NAD) for pancreatic cancer, faces limitations due to drug resistance.Characterizing pancreatic cancer cells' transport characteristics may help identify the mechanisms behind drug resistance, and develop more effective therapeutic strategies.Therefore, in this study, we aimed to determine the nucleoside transport properties of Panc-1 cells, one of the commonly used pancreatic adenocarcinoma cell lines.Materials and Methods: To assess the presence of equilibrative nucleoside transporter-1 (ENT-1) in Panc-1 cells, we performed immunofluorescence staining, western blot analysis, and S-(4-nitrobenzyl)-6-thioinosine (NBTI) binding assays.We also conducted standard uptake assays to measure the sodium-independent uptake of [3H]-labeled chloroadenosine, hypoxanthine, and uridine.In addition, we determined the half-maximal inhibitory concentration (IC 50 ) of gemcitabine.Statistical analyses were performed using GraphPad Prism version 8.0 for Windows.Results: The sodium-independent uptake of [3H]-labeled chloroadenosine, hypoxanthine, and uridine was measured using standard uptake assays, and the transport rates were determined as 111.1 3.4 pmol/mg protein/10 s, 62.5 4.8 pmol/mg protein/10 s, and 101.3 2.5 pmol/mg protein/10 s, respectively.Furthermore, the presence of ENT-1 protein was confirmed using NBTI binding assays (B max 1.52 0.1 pmol/mg protein; equilibrium dissociation constant 0.42 0.1 nM).Immunofluorescence assays and western blot analysis also revealed ENT-1 in Panc-1 cells.The determined IC 50 of gemcitabine in Panc-1 cells was 2 M, indicating moderate sensitivity.Conclusion: These results suggest that Panc-1 is a suitable preclinical cellular model for studying NAD transport properties and potential therapies in pancreatic cancer and pharmaceutical research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".